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A number of computational models have explained the behavior of dopamine neurons in terms of temporal difference learning.
Previous models have explained micron-sized dust observed at ∼10 cm above the surface, by suggesting that charged grains "levitate" in the local electric field; however this cannot account for observations of 0.1 μm-scale grains at ∼100 km altitude.
Some experimental models have explained the role of apoptosis in AKI setting.
Population-genetic models have explained the pattern of variation in human genetic diversity, with a decrease in heterozygosity at a greater distance from Africa, in relation to the relatively recent history of human migrations starting from an African origin.
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The typical horse-race model has explained about 50 percent of voting results during this period (and closer to 70 percent when you take a consensus of them).
A similar stimulus scaling model has explained effects of neural adaptation, which suggests that adaptation may account for the observed difference between rapid and spaced designs.
Climate models haven't explained this seeming contradiction to anyone's satisfaction and climate change deniers tout that failure early and often.
When students have finished their models, have them explain the form and function of each part to the class.
Taken together, our previous and current findings that alcohol suppresses Nrf2-ARE signaling in these complementary experimental models have helped explain an initial paradox.
In this paper a general methodology for modeling the components with mechanistic models has been explained and is further illustrated with an example component.
The metallic bonding present in the thin film models has been explained by electron localized function and density of state analysis.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com